Source code for pytorch_extra_mhirano.nn.pe

import math

import torch
import torch.nn as nn

# thank for https://pytorch.org/tutorials/beginner/transformer_tutorial.html


class PositionalEncoding(nn.Module):
    pe: torch.Tensor

    def __init__(self, d_model: int, dropout: float = 0.1, max_len: int = 5000) -> None:
        super(PositionalEncoding, self).__init__()
        self.dropout = nn.Dropout(p=dropout)

        pe = torch.zeros(max_len, d_model)
        position = torch.arange(0, max_len, dtype=torch.float).unsqueeze(1)
        div_term = torch.exp(
            torch.arange(0, d_model, 2).float() * (-math.log(10000.0) / d_model)
        )
        pe[:, 0::2] = torch.sin(position * div_term)
        pe[:, 1::2] = torch.cos(position * div_term)
        pe = pe.unsqueeze(0).transpose(0, 1)
        self.register_buffer("pe", pe)

    def forward(self, x: torch.Tensor) -> torch.Tensor:
        x = x + self.pe[: x.size(0), :]
        return self.dropout(x)